Abstract A042: Evolution of resistance in brain tumors: Effects of the blood brain barrier
Bibliographic record
Abstract
Abstract Background: Therapeutic treatment of brain tumors is uniquely challenging due to the presence of the blood brain barrier (BBB), which impedes drug penetration of the brain. This typically results in lower drug concentrations and slower time to steady-state in the brain relative to the body. In this analysis, we investigate the effects of the blood brain barrier on the evolution of resistance in brain tumors and accordingly seek optimal drug transport and clearance properties. Methods: To investigate the relationship between a drug’s BBB penetration parameters and its efficacy against brain tumors, we simulated drug penetration and tumor response in terms of total volume and resistant fraction. Brain pharmacokinetics (PK) are simulated by a two-compartment model in which the body and brain are represented. A series of differential equations transfer between compartments—across the blood brain barrier—and correspond to active and passive transport. Drug clearance in the brain and body are also considered. The tumor kinetics model consists of sensitive and resistance cells which are in competition, represented by a logistic growth function. For sensitive cells, the growth rate is reduced by the concentration of drug while resistant cells are unaffected. Results: We demonstrate that drug PK in the brain is characterized by a latency phase followed by steady-state dynamics. The tumor growth may continue during this latency. As the drug exerts its effect, sensitive cells die off. As the sensitive population is reduced, the effect of drug properties such as transport across the BBB and clearance diminishes. In general, the effect of active transport into the brain was found to be small compared to passive diffusion. Conclusions: Due to a longer time-to-steady state in the brain, therapeutic concentrations are reached more slowly in the brain. BBB penetration parameters impact tumor volume in the treatment phase where sensitive cells are present in significant number. Citation Format: Madison Stoddard, Lin Yuan, T Ryan. Gregory, Arijit Chakravarty. Evolution of resistance in brain tumors: Effects of the blood brain barrier [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2025 Oct 22-26; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2025;24(10 Suppl):Abstract nr A042.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".